Submission

Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace

In [5]:
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px

#Import pandas 
import pandas as pd 


init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
In [6]:
#load data
df = px.data.gapminder()
df.head()
Out[6]:
country continent year lifeExp pop gdpPercap iso_alpha iso_num
0 Afghanistan Asia 1952 28.801 8425333 779.445314 AFG 4
1 Afghanistan Asia 1957 30.332 9240934 820.853030 AFG 4
2 Afghanistan Asia 1962 31.997 10267083 853.100710 AFG 4
3 Afghanistan Asia 1967 34.020 11537966 836.197138 AFG 4
4 Afghanistan Asia 1972 36.088 13079460 739.981106 AFG 4

Question 1:

Recreate the barplot below that shows the population of different continents for the year 2007.

Hints:

  • Extract the 2007 year data from the dataframe. You have to process the data accordingly
  • use plotly bar
  • Add different colors for different continents
  • Sort the order of the continent for the visualisation. Use axis layout setting
  • Add text to each bar that represents the population
In [7]:
#Copy code from the lab assignment 'Data Visualisation'
df2007 = df[df['year'] == 2007]

#Sum population per continent and make new dataframe 
df2007continent = df2007.groupby('continent').sum()
df2007continent = pd.DataFrame(df2007continent)

df2007continent.head()


#Create figure and make different colors for each bar
#Order according to population
figurebar = px.bar(df2007continent, x='pop', orientation='h', color=df2007continent.index)
figurebar.update_layout(yaxis={'categoryorder':'total ascending'})
figurebar.show()

<ipython-input-7-a8cdf134e35c>:5: FutureWarning:

The default value of numeric_only in DataFrameGroupBy.sum is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.

Question 2:

Sort the order of the continent for the visualisation

Hint: Use axis layout setting

In [8]:
#Same as question 1
figurebar = px.bar(df2007continent, x='pop', orientation='h', color=df2007continent.index)
figurebar.update_layout(yaxis={'categoryorder':'total ascending'})
figurebar.show()

Question 3:

Add text to each bar that represents the population

In [9]:
#Same as question 1 
figurebar = px.bar(df2007continent, x='pop', orientation='h', color=df2007continent.index)
figurebar.update_layout(yaxis={'categoryorder':'total ascending'})
figurebar.show()

Question 4:

Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years

In [31]:
df = px.data.gapminder()
fig = px.histogram(df, x="pop", y="continent", animation_frame="year", 
             color="continent", 
             range_x = [0,4000000000]    #Define range such that the graph evolves nicely over time
           )
fig.update_yaxes(categoryorder = 'max ascending') #Bars in ascending order
fig.show()

Question 5:

Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years

In [27]:
df = px.data.gapminder()

#Instead of y=continent we now use y=country
fig = px.histogram(df, x="pop", y="country", animation_frame="year",
             color="country", 
             range_x = [0,4000000000]    #Define range such that the graph evolves nicely over time
           )

fig.update_yaxes(categoryorder = 'max ascending')
fig.show()

Question 6:

Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation

In [32]:
df = px.data.gapminder()

#Instead of y=continent we now use y=country
fig = px.histogram(df, x="pop", y="country", animation_frame="year", 
             color="country", 
             range_x = [0,4000000000], 
             height = 1000              
           )

fig.update_yaxes(categoryorder = 'max ascending')
fig.show()

Question 7:

Show only the top 10 countries in the animation

Hint: Use the axis limit to set this.

In [49]:
df = px.data.gapminder()
df['country'].nunique()

#There are 142 countries, so take 133 up and including 142
Out[49]:
142
In [52]:
df = px.data.gapminder()

#Instead of y=continent we now use y=country
fig = px.histogram(df, x="pop", y="country", animation_frame="year", 
             color="country", 
             range_x = [0,4000000000], 
             range_y = [131.5,141.5],    #Take top 10 
             height = 1000           
           )

fig.update_yaxes(categoryorder = 'max ascending')


fig.show()
In [ ]: